[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2533":3,"related-2533":113},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":78,"slug":81,"view_count":82,"doi":83,"paper":84,"created_at":112},2533,"Quantifying the Environmental Impact of Artisanal and Small‐Scale Mining: An Integrated Approach for Sustainable Development Insights","https:\u002F\u002Fdoi.org\u002F10.1002\u002Fsd.71693","ABSTRACT Artisanal and small‐scale mining (ASM) provides livelihoods for over 44.5 million people globally, yet its largely unregulated nature causes severe environmental degradation in host communities. In Nigeria, where ASM accounts for over 90% of solid mineral production, the sector increasingly encroaches on agricultural land. Despite growing recognition of ASM's environmental impacts across West Africa, no study has yet applied the novel SDGSAT‐1 satellite purpose‐built for SDG monitoring at 10 m resolution to quantify ASM land degradation in Nigeria, and few studies simultaneously integrate multi‐sensor remote sensing, in‐situ soil contamination assessment, and hydrological transport modelling within a single integrated framework. This study addresses that gap. This study integrates SDGSAT‐1 Multispectral Imager and Landsat 9 imagery (both acquired 12 January 2024) with field‐based soil sampling (November 2023, dry season) and GIS hydrological modelling for Igbojaiye community, Oyo State, Nigeria. Eight vegetation, water and soil indices (NDVI, EVI, SAVI, TSAVI, TVI, NDWI, BSI) and Land Surface Temperature were derived from satellite imagery. Soil samples from eight mining‐affected points and four undisturbed control points were analyzed for physicochemical properties and heavy metals (Fe, Pb, Zn) using Atomic Absorption Spectrometry. Contamination Factor, Geoaccumulation Index, Pollution Load Index, and a Potential Ecological Risk Index were computed. A Digital Elevation Model was used to delineate contaminant transport pathways. ASM‐affected areas exhibited severe vegetation loss (68% of land within 500 m of mining pits classified as Degraded; mean NDVI −0.08 vs. +0.18 in control areas) and elevated Land Surface Temperature (mean 35.2°C ± 1.3°C vs. 28.9°C ± 0.8°C in controls). Mining soils showed markedly degraded physicochemical properties (organic carbon 4× lower, moisture 5× lower, pH more acidic). Lead exhibited very high contamination (mean Contamination Factor 10.0; Geoaccumulation Index Class 3: moderately to heavily contaminated) with a statistically significant distance‐decay gradient ( r = −0.60, p = 0.04). No metal exceeded WHO\u002FFAO soil limits in absolute terms. Hydrological modelling identified direct flow pathways from mining pits to downstream farmland and waterbodies. ASM in Igbojaiye initiates a cascade of compounding degradation, soil toxicity, microclimatic disruption, and hydrological pollutant dispersal that collectively undermine agricultural productivity and water security, directly impeding SDGs 2, 6, 13, and 15. This study represents one of the first applications of SDGSAT‐1 for ASM monitoring in Nigeria, establishing a replicable multi‐sensor framework for evidence‐based environmental governance of ASM in data‐scarce sub‐Saharan African contexts. Remediation priorities include sediment traps at mining pit outflows, phytoremediation with native metal‐tolerant species, and satellite‐based biannual monitoring protocols.","手工和小规模采矿（ASM）为全球超过4450万人提供了生计，但其基本上不受监管的性质对所在社区造成了严重的环境退化。在尼日利亚，手工和小规模采矿占固体矿产产量的90%以上，该行业日益侵占农业用地。尽管西非地区对ASM环境影响的认知不断增加，但尚无研究应用专为可持续发展目标监测而设计的10米分辨率SDGSAT-1卫星来量化尼日利亚的ASM土地退化，且很少有研究将多传感器遥感、原位土壤污染评估和水文输移建模同时整合于单一综合框架中。本研究填补了这一空白。本研究将SDGSAT-1多光谱成像仪和Landsat 9影像（均于2024年1月12日获取）与实地土壤采样（2023年11月，旱季）及GIS水文建模相结合，以尼日利亚奥约州Igbojaiye社区为研究区。从卫星影像中提取了八个植被、水体和土壤指数（NDVI、EVI、SAVI、TSAVI、TVI、NDWI、BSI）及地表温度。采用原子吸收光谱法对来自八个受采矿影响点和四个未受干扰对照点的土壤样品进行了理化性质和重金属（Fe、Pb、Zn）分析。计算了污染因子、地累积指数、污染负荷指数和潜在生态风险指数。利用数字高程模型划定了污染物输移路径。受ASM影响的区域表现出严重的植被丧失（采矿坑500米范围内68%的土地被归类为退化；NDVI均值为−0.08，对照区为+0.18）和升高的地表温度（均值35.2°C ± 1.3°C，对照区为28.9°C ± 0.8°C）。矿区土壤理化性质显著退化（有机碳低4倍，含水量低5倍，pH更偏酸性）。铅表现出极高的污染水平（污染因子均值10.0；地累积指数3级：中度至重度污染），并具有统计学显著的距离衰减梯度（r = −0.60，p = 0.04）。就绝对值而言，无金属超过WHO\u002FFAO土壤限值。水文建模识别出从采矿坑到下游农田和水体的直接径流路径。Igbojaiye的ASM引发了一系列叠加退化、土壤毒性、微气候扰动和水文污染物扩散的级联效应，共同导致",null,"Sustainable Development","2026-09-14T00:00:00Z","论文",10,false,82,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,23,19,14,8,1,"首次将SDGSAT-1遥感与土壤、水文模型整合量化尼日利亚小规模采矿对农地的复合退化，方法可复用于数据稀缺地区农业环境治理，对农业遥感与耕地保护主题有聚合价值。",[25],{"name":10,"url":6},[27,28,29,30,31],"数字乡村","可持续发展","耕地保护","遥感监测","农业环境",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":46},[45,53,61,68,73],{"code":33,"score":13,"supported":46,"title":47,"abstract":48,"tags":52},true,[],[49,50,51],"遥感","remote sensing","multispectral",[30],{"code":54,"score":55,"supported":46,"title":56,"abstract":57,"tags":60},"H2",6,[],[58,59],"土壤","soil",[],{"code":62,"score":63,"supported":46,"title":64,"abstract":65,"tags":67},"I4",3,[],[66],"GIS",[],{"code":69,"score":22,"supported":14,"title":70,"abstract":71,"tags":72},"H1",[],[],[29],{"code":74,"score":22,"supported":14,"title":75,"abstract":76,"tags":77},"I6",[],[],[27],[79,80],"可持续发展 农业环境 数字乡村 耕地保护","可持续发展 农业环境","可持续发展农业环境数字乡村耕地保护-2533",0,"10.1002\u002Fsd.71693",{"doi":83,"openalex_id":85,"authors":86,"venue":10,"cited_by_count":82,"oa_url":9,"card":105,"direction":109,"ingested_from":111},"W7213179964",[87,90,92,95,97,99,102],{"name":88,"orcid":89},"Sehinde Akinbiola","https:\u002F\u002Forcid.org\u002F0000-0001-9602-2420",{"name":91,"orcid":9},"Julia Blumensaat",{"name":93,"orcid":94},"Ayobami Salami","https:\u002F\u002Forcid.org\u002F0000-0002-7567-9762",{"name":96,"orcid":9},"Jürgen Runge",{"name":98,"orcid":9},"Tella Iyiola",{"name":100,"orcid":101},"Olamide Omolafe Ogunremi","https:\u002F\u002Forcid.org\u002F0000-0002-6776-4983",{"name":103,"orcid":104},"Ayomide Emmanuel Olubaju","https:\u002F\u002Forcid.org\u002F0000-0003-2118-6759",{"tldr":106,"method":107,"finding":108,"direction":109,"opportunity":110},"用SDGSAT-1等多源遥感与实地采样量化尼日利亚手工采矿对土地与农田的环境退化。","SDGSAT-1与Landsat 9影像、8种植被水体土壤指数、土壤重金属AAS","矿区植被严重退化、地表温度升高、铅污染极重，并存在向农田与水体扩散的水文通道。","农业遥感与作物表型","可将SDGSAT-1 10米影像与土壤、水文模型耦合，构建矿区农田退化与重金属风险的早期预警框架。","openalex","2026-09-15T23:30:20.829150Z",{"total":55,"page":22,"page_size":55,"items":114},[115,177,264,324,393,453],{"id":116,"title":117,"url":118,"summary":119,"summary_zh":120,"content":9,"source_name":121,"source_url":118,"published_at":122,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":123,"score_detail":124,"sources":128,"tags":130,"primary_topic":134,"secondary_topics":135,"classification":136,"search_phrases":154,"slug":157,"view_count":158,"doi":159,"paper":160,"created_at":176},4588,"Integrating terrestrial and marine remote sensing indicators to estimate subnational economic output","https:\u002F\u002Fdoi.org\u002F10.1080\u002F01431161.2026.2743115","Subnational economic data remain scarce across much of the Global South, particularly in fragmented island and coastal geographies, thereby constraining the capacity of researchers and policymakers to monitor local economic conditions. This study proposes and empirically evaluates a four-proxy remote sensing framework for subnational gross domestic product (GDP) estimation. The framework extends the established Night-time Lights (NTL)–Normalised Difference Vegetation Index (NDVI)–Forest Loss (FL) approach by incorporating sea surface Chlorophyll-a (CHLA) as a marine fisheries proxy. This achieves full proxy coverage across the non-agriculture, forestry, and fisheries sector through NTL, agriculture through NDVI, forestry through FL, and marine fisheries through CHLA. The empirical analysis employs Multiscale Geographically Weighted Regression (MGWR) and pooled ordinary least squares (OLS) across 102 regencies and cities in Sulawesi and Maluku, eastern Indonesia, over 2015–2024, with a province-level panel extending to 2002–2024. The stepwise MGWR R2 rises from 0.468 (NTL only) to 0.543 (NTL, NDVI, and FL) to 0.561 (full model), with a pooled Pearson correlation of 0.760. CHLA is positive and significant at both spatial scales after conditioning on all terrestrial proxies, confirmed by OLS coefficients of 0.029 at the regency\u002Fcity level and 0.148 at the province level, significant at the 0.1% and 1% levels respectively. All proxy relationships replicate in direction and significance across scales and over the 23-year panel. The framework provides a freely replicable tool for subnational economic monitoring in data-scarce coastal and island settings, with direct applicability to marine-dependent primary sector economies globally.","在全球南方的大部分地区，尤其是碎片化的岛屿和沿海地理区域，地方经济数据仍然稀缺，从而制约了研究者和政策制定者监测地方经济状况的能力。本研究提出并实证评估了一个用于地方国内生产总值（GDP）估算的四代理变量遥感框架。该框架在已有的夜间灯光（NTL）—归一化植被指数（NDVI）—森林损失（FL）方法基础上，引入海表叶绿素a（CHLA）作为海洋渔业代理变量。由此实现了对非农、林业和渔业部门的代理变量全覆盖：NTL对应非农部门，NDVI对应农业，FL对应林业，CHLA对应海洋渔业。实证分析采用多尺度地理加权回归（MGWR）和混合普通最小二乘法（OLS），覆盖印度尼西亚东部苏拉威西和马鲁古的102个县和市，时间范围为2015—2024年，并辅以延伸至2002—2024年的省级面板数据。逐步MGWR的R²从0.468（仅NTL）升至0.543（NTL、NDVI和FL）再升至0.561（全模型），混合皮尔逊相关系数为0.760。在控制所有陆地代理变量后，CHLA在两个空间尺度上均为正向且显著，OLS系数在县\u002F市级为0.029、省级为0.148，分别在0.1%和1%水平上显著。所有代理变量关系在不同尺度和23年面板期间在方向和显著性上均得到重复验证。该框架为数据稀缺的沿海和岛屿地区的地方经济监测提供了一个可自由复制的工具，并可直接适用于全球依赖海洋的初级产业经济体。","International Journal of Remote Sensing","2026-10-09T00:00:00Z",81,{"impact":17,"substance":125,"depth":17,"authority":20,"freshness":126,"relevant":22,"comment":127},22,9,"将叶绿素a纳入遥感代理框架估算次国家级GDP，方法新颖、数据扎实，对数据稀缺沿海岛屿地区的农业与渔业经济监测有直接参考价值。",[129],{"name":121,"url":118},[27,131,30,132,133],"农业遥感","渔业经济","GDP估算",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":137},{"candidates":138,"agricultural_evidence":46},[139,144,150],{"code":33,"score":140,"supported":46,"title":141,"abstract":142,"tags":143},16,[50],[49,50],[131,30],{"code":145,"score":63,"supported":46,"title":146,"abstract":147,"tags":149},"D",[],[148],"渔业",[],{"code":74,"score":22,"supported":14,"title":151,"abstract":152,"tags":153},[],[],[27],[155,156],"苏拉威西 马鲁古 遥感 GDP","叶绿素a 海洋渔业 遥感","苏拉威西马鲁古遥感GDP-4588",2,"10.1080\u002F01431161.2026.2743115",{"doi":159,"openalex_id":161,"authors":162,"venue":121,"cited_by_count":82,"oa_url":9,"card":171,"direction":109,"ingested_from":111},"W7221189467",[163,166,168],{"name":164,"orcid":165},"Laurenz Thiele","https:\u002F\u002Forcid.org\u002F0009-0009-9294-1337",{"name":167,"orcid":9},"Amanus Khalifafilardy Yunus",{"name":169,"orcid":170},"Rahmatia","https:\u002F\u002Forcid.org\u002F0009-0009-7550-9243",{"tldr":172,"method":173,"finding":174,"direction":109,"opportunity":175},"提出融合陆地与海洋遥感指标的四代理框架，估算印尼东部次国家级GDP。","用夜间灯光、NDVI、森林损失与叶绿素a，结合MGWR和OLS分析102个县市。","加入叶绿素a后模型R²从0.543升至0.561，海洋渔业代理显著提升经济估算精度。","可将海洋遥感代理拓展至其他沿海地区，并耦合渔业产量与贸易数据验证经济监测普适性。","2026-10-10T23:30:28.117529Z",{"id":178,"title":179,"url":180,"summary":181,"summary_zh":182,"content":9,"source_name":183,"source_url":180,"published_at":184,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":185,"score_detail":186,"sources":190,"tags":192,"primary_topic":196,"secondary_topics":200,"classification":202,"search_phrases":223,"slug":226,"view_count":82,"doi":227,"paper":228,"created_at":263},4366,"Article topic: comprehensive assessment of soil and flora contamination by heavy metals in the zone of influence of the Nikolaevskaya enrichment plant","https:\u002F\u002Fdoi.org\u002F10.51886\u002F1999-740x_2026_3_46","Agricultural lands in East Kazakhstan region cover a significant area, with large portions of pasture and cropland situated in close proximity to operating industrial facilities. Despite this, no comprehensive integrated assessment combining remote sensing, ground-based soil monitoring, and flora survey had previously been conducted for the zone of influence of the Nikolaevskaya enrichment plant. This study aimed to fill that gap by a 40-year land cover analysis (1985-2024) using publicly available satellite data processed in Google Earth Engine with soil sampling and vegetation surveys across 17 sites. Soil analyses revealed not only elevated heavy metal concentrations but also a sharp pH decrease, conditions under which heavy metals become significantly more mobile and available for plant uptake. Technosol formation was observed at multiple sampling points, indicating a permanent transformation of the natural soil profile. The flora survey recorded 72 species from 62 genera, with ruderal and synanthropic species domina-ting disturbed habitats and native species persisting only at control points more distant from the facility. Taken together, these findings point to ongoing ecosystem degradation and raise concrete concerns for the regional food chain given the pastureland and cropland adjacent to the plant.","东哈萨克斯坦地区的农业用地面积广阔，其中大片牧场和农田与正在运营的工业设施相距不远。尽管如此，此前尚未针对尼古拉耶夫斯克选矿厂影响区域开展过将遥感、地面土壤监测与植物区系调查相结合的综合评估。本研究旨在填补这一空白，通过为期40年的土地覆盖分析（1985—2024年），利用Google Earth Engine处理的公开卫星数据，并结合17个样点的土壤采样与植被调查。土壤分析不仅揭示了重金属浓度升高，还发现pH值急剧下降，在这种条件下，重金属的迁移性和植物可利用性显著增强。在多个采样点观察到技术土（Technosol）的形成，表明自然土壤剖面发生了永久性改变。植物区系调查共记录到62属72种植物，其中扰动生境以杂草类和伴人植物物种为主，原生物种仅存于距设施较远的对照点。综合来看，这些发现表明生态系统正在持续退化，并且鉴于该厂邻近牧场和农田，对区域食物链构成了切实的担忧。","Pochvovedenie i agrokhimiya","2026-10-05T00:00:00Z",73,{"impact":187,"substance":125,"depth":17,"authority":188,"freshness":21,"relevant":22,"comment":189},12,13,"结合40年遥感与地面采样的重金属污染综合评估，方法扎实、结论具体，但属区域案例研究，公共影响有限。",[191],{"name":183,"url":180},[29,193,30,194,195],"农业生态","Google Earth Engine","土壤重金属",{"code":54,"slug":59,"name":197,"path":198,"parent_code":199},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",[201],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":203},{"candidates":204,"agricultural_evidence":46},[205,210,214,218],{"code":54,"score":206,"supported":46,"title":207,"abstract":208,"tags":209},15,[59],[58,59],[195],{"code":33,"score":21,"supported":46,"title":211,"abstract":212,"tags":213},[],[49,50],[194,30],{"code":69,"score":22,"supported":14,"title":215,"abstract":216,"tags":217},[],[],[29],{"code":219,"score":22,"supported":14,"title":220,"abstract":221,"tags":222},"H6",[],[],[193],[224,225],"Nikolaevskaya 选矿厂 土壤污染","东哈萨克斯坦 农田 重金属","Nikolaevskaya选矿厂土壤污染-4366","10.51886\u002F1999-740x_2026_3_46",{"doi":227,"openalex_id":229,"authors":230,"venue":183,"cited_by_count":82,"oa_url":256,"card":257,"direction":109,"ingested_from":111},"W7220713350",[231,234,236,239,242,245,248,251,254],{"name":232,"orcid":233},"Yuliya Tugunova","https:\u002F\u002Forcid.org\u002F0009-0006-1037-1480",{"name":235,"orcid":9},"M. Altynbayeva",{"name":237,"orcid":238},"Жанар Абилда","https:\u002F\u002Forcid.org\u002F0000-0001-8505-5243",{"name":240,"orcid":241},"Рахим Канат","https:\u002F\u002Forcid.org\u002F0009-0009-2418-5920",{"name":243,"orcid":244},"Abylay Begaly","https:\u002F\u002Forcid.org\u002F0009-0009-2848-336X",{"name":246,"orcid":247},"D. Kairkhanov","https:\u002F\u002Forcid.org\u002F0009-0006-1017-1980",{"name":249,"orcid":250},"Iskander Isgandarov","https:\u002F\u002Forcid.org\u002F0009-0001-4386-3303",{"name":252,"orcid":253},"ELENA A. ISAKOVA","https:\u002F\u002Forcid.org\u002F0000-0002-9056-6504",{"name":255,"orcid":9},"Kh. Choi","https:\u002F\u002Fjournal.soil.kz\u002Fjour\u002Farticle\u002Fdownload\u002F1135\u002F802",{"tldr":258,"method":259,"finding":260,"direction":261,"opportunity":262},"综合遥感、土壤采样与植被调查，评估哈萨克斯坦一选矿厂影响区40年重金属污染与生态退化。","Google Earth Engine处理1985-2024卫星数据，结合17个","土壤重金属升高且pH骤降，重金属迁移性增强，形成技术土，植被以杂草为主，威胁食物链。","农业绿色发展与碳","可延伸研究重金属活化与pH耦合机制，并构建污染区农田食物链风险预警模型。","2026-10-07T23:30:29.146414Z",{"id":265,"title":266,"url":267,"summary":268,"summary_zh":269,"content":9,"source_name":270,"source_url":267,"published_at":271,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":272,"score_detail":273,"sources":276,"tags":278,"primary_topic":281,"secondary_topics":282,"classification":283,"search_phrases":303,"slug":306,"view_count":307,"doi":308,"paper":309,"created_at":323},3907,"Land use and land cover change in the Okavango Delta, Botswana: integrating remote sensing and community perspectives on change drivers","https:\u002F\u002Fdoi.org\u002F10.1080\u002F0035919x.2026.2731206","Land use and land cover change is a complex process triggered by either natural or anthropogenic factors. It has important implications for socioeconomic development and environmental sustainability. The present study assessed the dynamics of LULC in Shakawe and Gumare villages of northern Botswana from 1990 to 2023. The study also analysed stakeholders’ perceptions regarding the causes of LULC transformations. The drivers and patterns of land use and land cover change (LULCC) were identified by adopting satellite imagery analysis and a survey approach. The study employed supervised digital image classification and change detection techniques in combination with structured surveys to capture stakeholders’ perceptions. The results show urbanisation and agriculture are the dominant drivers of LULCC, leading to notable alterations in built-up areas, vegetation cover, and infrastructure development. The growth of population and economic activities play a role in shaping LULC dynamics in the study area. Findings also show that the built-up areas in Shakawe increased from 0.97 km2 to 2.02 km2 and from 0.26 km2 to 1.30 km2 in Gumare. Barren land was reduced from 10.9 km2 in 1990 to 4.02 km2 in 2023, and shrubs and trees decreased from 20.53 km2 in 1990 to 16.21 km2 in 2023. A Kruskal–Wallis test revealed a statistically significant difference (X2 = 28.4; p \u003C 0.001) in the way people from different ethnic groups perceived factors influencing LULC. The results highlight the interplay between environmental change and human activities, necessitating sustainable land management practices and highly informed decision-making. The research further highlights the importance of local-level analysis of how LULC patterns and change drivers are understood, particularly in regions experiencing high population growth and resource utilisation. By presenting temporal and spatial patterns of LULC, this research paper contributes to the broader knowledge of land use change processes and policy development aimed at environmental resilience and community well-being.","土地利用与土地覆盖变化是由自然或人为因素触发的复杂过程，对社会经济发展和环境可持续性具有重要影响。本研究评估了博茨瓦纳北部沙卡韦和古马雷村庄1990年至2023年土地利用与土地覆盖（LULC）的动态变化，同时分析了利益相关者对土地利用与土地覆盖变化（LULCC）驱动因素的认知。研究采用卫星影像分析和问卷调查方法，识别了LULCC的驱动因素和变化模式。研究运用监督式数字图像分类和变化检测技术，结合结构化问卷调查，以获取利益相关者的认知。结果表明，城市化和农业是LULCC的主要驱动因素，导致建成区、植被覆盖和基础设施建设发生显著变化。人口增长和经济活动在塑造研究区LULC动态中发挥了重要作用。研究结果还显示，沙卡韦的建成区面积从0.97 km²增至2.02 km²，古马雷从0.26 km²增至1.30 km²。裸地从1990年的10.9 km²减少至2023年的4.02 km²，灌木和乔木从1990年的20.53 km²减少至2023年的16.21 km²。Kruskal–Wallis检验表明，不同族群对影响LULC因素的认知存在统计学显著差异（X² = 28.4；p \u003C 0.001）。研究结果凸显了环境变化与人类活动之间的相互作用，亟需可持续的土地管理实践和高度科学的决策。本研究进一步强调了地方层面分析LULC格局及变化驱动因素认知的重要性，尤其是在人口快速增长和资源利用强度较高的地区。通过呈现LULC的时间和空间格局，本文为土地利用变化过程的广泛知识体系以及旨在增强环境韧性和社区福祉的政策制定作出了贡献。","Transactions of the Royal Society of South Africa","2026-09-29T00:00:00Z",65,{"impact":21,"substance":274,"depth":140,"authority":188,"freshness":21,"relevant":22,"comment":275},20,"遥感与社区调查结合的土地利用变化研究，方法扎实、数据具体，但属境外区域案例，对国内三农信息化参考价值有限。",[277],{"name":270,"url":267},[27,131,279,30,280],"可持续农业","土地利用变化",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":284},{"candidates":285,"agricultural_evidence":46},[286,290,294,299],{"code":33,"score":13,"supported":46,"title":287,"abstract":288,"tags":289},[50],[],[131,30],{"code":219,"score":22,"supported":14,"title":291,"abstract":292,"tags":293},[],[],[280],{"code":295,"score":22,"supported":14,"title":296,"abstract":297,"tags":298},"H8",[],[],[279],{"code":74,"score":22,"supported":14,"title":300,"abstract":301,"tags":302},[],[],[27],[304,305],"Okavango Delta 土地利用变化","博茨瓦纳 遥感 社区感知","OkavangoDelta土地利用变化-3907",4,"10.1080\u002F0035919x.2026.2731206",{"doi":308,"openalex_id":310,"authors":311,"venue":270,"cited_by_count":82,"oa_url":267,"card":318,"direction":109,"ingested_from":111},"W7214955668",[312,315],{"name":313,"orcid":314},"Reniko Gondo","https:\u002F\u002Forcid.org\u002F0000-0002-0957-0179",{"name":316,"orcid":317},"Oluwatoyin Dare Kolawole","https:\u002F\u002Forcid.org\u002F0000-0002-3977-8747",{"tldr":319,"method":320,"finding":321,"direction":109,"opportunity":322},"结合遥感与社区调查，分析博茨瓦纳奥卡万戈三角洲1990-2023年土地利用变化及驱动因素。","监督分类与变化检测遥感影像，结合结构化问卷调查和Kruskal-Wallis检验","城市化和农业是主要驱动力，建设用地增加、林灌减少，不同族群对驱动因素感知有显著差异。","可探索多源遥感与社区感知融合的LULC驱动机制建模，并关注族群差异对土地管理的影响。","2026-10-01T23:30:30.841433Z",{"id":325,"title":326,"url":327,"summary":328,"summary_zh":329,"content":9,"source_name":330,"source_url":327,"published_at":331,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":82,"score_detail":332,"sources":334,"tags":336,"primary_topic":339,"secondary_topics":340,"classification":345,"search_phrases":371,"slug":374,"view_count":126,"doi":375,"paper":376,"created_at":392},3071,"Urban Influence on Landscape Transformation and Land Cover Interactions During Urban Expansion (1972–2022): A Remote Sensing and GIS-Based Analysis","https:\u002F\u002Fdoi.org\u002F10.2478\u002Fjlecol-2026-0038","Abstract This study investigates how urban expansion influences land cover dynamics. An interactive analytical approach was adopted to examine the transitions among built-up areas, cropland, and bare land throughout the urbanization process. Remote Sensing and GIS techniques, in conjunction with the Land Transfer Matrix (LTM), Landscape Metrics (LM), Multi-buffer Ring (MBR) and complementary spatial tools, were employed to analyze the city of Tiaret in Algeria over the past half century (1972-2022). The results reveal a marked intensification of urbanization, with an Overall Average Annual Urban Expansion Rate (OA-AUER) of 28.3 ha and a concurrent rise in bare land driven by cropland conversion under urban pressure. Notably, 89.4 % of cropland loss initially transitions into bare land, while subsequent urban development originates from cropland (52 %) and bare land (47 %). The observed density patterns in peripheral areas confirm the significant influence of the urban core on surrounding land-cover transformations. These findings elucidate the urbanization process while considering the transitional role of bare land and further explain diffusion coalescence process. Further empirical research is recommended to refine theoretical frameworks on landscape transformation dynamics and to inform policies aimed at mitigating bare-land expansion in peri-urban areas, controlling cropland urbanization, and planning sustainable urban growth.","摘要 本研究探讨城市扩张如何影响土地覆盖动态。采用交互式分析方法，考察城市化进程中建成区、耕地和裸地之间的转换。运用遥感与地理信息系统技术，结合土地转移矩阵（LTM）、景观格局指数（LM）、多缓冲环（MBR）及辅助空间工具，对阿尔及利亚提亚雷特市过去半个世纪（1972—2022年）的变化进行了分析。结果表明，城市化显著加剧，年均城市扩张总面积率（OA-AUER）为28.3公顷，同时在城市压力下耕地转换导致裸地同步增加。值得注意的是，89.4%的耕地损失最初转变为裸地，而随后的城市发展来源于耕地（52%）和裸地（47%）。外围区域观测到的密度格局证实了城市核心对周边土地覆盖变化的显著影响。这些发现阐明了城市化过程，同时考虑了裸地的过渡性作用，并进一步解释了扩散聚合过程。建议开展进一步实证研究，以完善景观转型动态的理论框架，并为旨在减缓城郊地区裸地扩张、控制耕地城市化以及规划可持续城市增长的政策提供依据。","Journal of Landscape Ecology","2026-09-19T00:00:00Z",{"impact":82,"substance":82,"depth":82,"authority":82,"freshness":82,"relevant":82,"comment":333},"该论文聚焦阿尔及利亚Tiaret市城市扩张与土地覆盖变化，属城市地理与遥感应用研究，与三农、农业信息化、智慧农业主题无直接关联，不建议进入每日精选。",[335],{"name":330,"url":327},[29,30,337,338],"土地利用","城市扩张",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[341],{"code":62,"slug":342,"name":343,"path":344,"parent_code":37},"gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis",{"status":40,"locked":14,"version":41,"method":42,"evidence":346},{"candidates":347,"agricultural_evidence":46},[348,352,357,363,367],{"code":33,"score":206,"supported":46,"title":349,"abstract":350,"tags":351},[50],[49,50],[30],{"code":62,"score":20,"supported":46,"title":353,"abstract":354,"tags":356},[66],[355,66],"地理信息",[],{"code":358,"score":63,"supported":46,"title":359,"abstract":360,"tags":362},"G2",[],[361],"land transfer",[],{"code":69,"score":22,"supported":14,"title":364,"abstract":365,"tags":366},[],[],[29],{"code":219,"score":22,"supported":14,"title":368,"abstract":369,"tags":370},[],[],[337],[372,373],"Tiaret 城市扩张 遥感","耕地 建设用地 转移矩阵","Tiaret城市扩张遥感-3071","10.2478\u002Fjlecol-2026-0038",{"doi":375,"openalex_id":377,"authors":378,"venue":330,"cited_by_count":82,"oa_url":386,"card":387,"direction":109,"ingested_from":111},"W7213652939",[379,381,383],{"name":380,"orcid":9},"Amina Kalbaza",{"name":382,"orcid":9},"Belkacem Marir",{"name":384,"orcid":385},"Farida Naceur","https:\u002F\u002Forcid.org\u002F0009-0004-1962-4937","https:\u002F\u002Freference-global.com\u002Fdownload\u002Farticle\u002F10.2478\u002Fjlecol-2026-0038.pdf",{"tldr":388,"method":389,"finding":390,"direction":109,"opportunity":391},"基于遥感与GIS分析阿尔及利亚提亚雷特1972—2022年城市扩张对景观与土地覆盖的影响。","遥感、GIS、土地转移矩阵、景观格局指数与多缓冲环分析。","耕地先转为裸地再被城市占用，城市核心显著驱动外围土地覆盖转变。","可延伸研究裸地作为耕地—城市转换中间态的机制，并构建城郊耕地流失预警模型。","2026-09-21T23:30:24.332177Z",{"id":394,"title":395,"url":396,"summary":397,"summary_zh":398,"content":9,"source_name":399,"source_url":396,"published_at":400,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":401,"score_detail":402,"sources":404,"tags":406,"primary_topic":407,"secondary_topics":408,"classification":409,"search_phrases":429,"slug":432,"view_count":158,"doi":433,"paper":434,"created_at":452},2784,"Monitoring & Evaluating of Urban Expansion and Its Impact on Land use Land Cover Change of Sargodha, Pakistan (2000-2025)","https:\u002F\u002Fdoi.org\u002F10.71317\u002Fjgst.2.9(s).2026.624","Urban growth is a significant land-use transition that is taking place in many rapidly growing cities, especially where the expansion is taking place on productive agricultural land. The purpose of this research was to explore the Spatio-temporal pattern of urban expansion and changes in land use\u002Fland cover (LULC) in Sargodha Tehsil, Pakistan, for the period 2000-2025. This study used the remote sensing and GIS techniques to analyze the satellite imageries of 6 years. These years include 2000, 2005, 2010, 2015, 2020 and 2025. The study area covered an expanse of 1536 km² and comprised four land use\u002Fland cover (LULC) classes, including agricultural land, built-up area, barren land, and water bodies. The study used supervised classification Maximum likelihood classifier (MLC) to identify the dominant land use and land cover types and determine the percentage of the region that was covered by each class. The results show that there is a growing trend in the built-up area throughout the years. It increased from 115 km² in 2000 to 180 km² in 2005, 233 km² in 2010, 297 km² in 2015, 361 km² in 2020, and 440 km² in 2025. Thus, it can be stated that there was an increase in the built-up area by 325 km² or 282.6% over the studied period. In contrast, the amount of farmland decreased from 1,014 km² to 815 km² or 199 km². The area of barren land decreased as well from 280 km² to 153 km². At the same time, there was no significant change in the amount of water bodies from 127 km² to 128 km². Findings reveal a significant change from a primarily agricultural region to a region with a considerable presence of developed areas and emphasize the increasing pressure on productive land. The research underlines the significance of planned urbanization, protection of productive agricultural lands, regular geospatial monitoring, and appropriate management of the periphery belt.","城市增长是许多快速发展的城市正在经历的重要土地利用转变，尤其是在生产力较高的农业用地上发生扩张的地区。本研究旨在探讨巴基斯坦萨戈达县（Sargodha Tehsil）2000—2025年期间城市扩张的时空格局及土地利用\u002F土地覆盖（LULC）变化。本研究采用遥感与GIS技术，对6个年份的卫星影像进行了分析，包括2000年、2005年、2010年、2015年、2020年和2025年。研究区面积为1536 km²，涵盖四种土地利用\u002F土地覆盖（LULC）类型，包括农业用地、建设用地、裸地和水体。研究采用监督分类中的最大似然分类器（MLC）识别主要土地利用与土地覆盖类型，并确定各类型所占区域百分比。结果表明，建设用地面积在各年份间呈持续增长趋势，从2000年的115 km²增至2005年的180 km²、2010年的233 km²、2015年的297 km²、2020年的361 km²，以及2025年的440 km²。因此可以认为，在研究期间建设用地面积增加了325 km²，增幅达282.6%。相比之下，农田面积从1014 km²减少至815 km²，减少了199 km²。裸地面积也从280 km²减少至153 km²。与此同时，水体面积从127 km²变化至128 km²，没有显著变化。研究结果揭示了该区域从以农业为主向建设用地显著增加的区域发生了重大转变，并凸显了生产性土地日益增大的压力。本研究强调了有计划城市化、保护生产性农业用地、定期地理空间监测以及对外围地带进行适当管理的重要性。","Journal of Global Social Transformation","2026-09-17T00:00:00Z",55,{"impact":21,"substance":17,"depth":20,"authority":55,"freshness":126,"relevant":22,"comment":403},"基于遥感与GIS的巴基斯坦城市扩张对农用地影响研究，数据翔实但属区域案例，对国内三农信息化参考价值有限。",[405],{"name":399,"url":396},[29,30,337,66,338],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":410},{"candidates":411,"agricultural_evidence":46},[412,417,421,425],{"code":33,"score":413,"supported":46,"title":414,"abstract":415,"tags":416},7,[],[49,50],[30],{"code":62,"score":307,"supported":46,"title":418,"abstract":419,"tags":420},[],[66],[66],{"code":69,"score":22,"supported":14,"title":422,"abstract":423,"tags":424},[],[],[29],{"code":219,"score":22,"supported":14,"title":426,"abstract":427,"tags":428},[],[],[337],[430,431],"土地利用 城市扩张 耕地保护 遥感监测","土地利用 城市扩张","土地利用城市扩张耕地保护遥感监测-2784","10.71317\u002Fjgst.2.9(s).2026.624",{"doi":433,"openalex_id":435,"authors":436,"venue":399,"cited_by_count":82,"oa_url":396,"card":447,"direction":109,"ingested_from":111},"W7213443079",[437,439,442,444],{"name":438,"orcid":9},"Muhammad Israr",{"name":440,"orcid":441},"Omar Riaz","https:\u002F\u002Forcid.org\u002F0000-0002-5391-109X",{"name":443,"orcid":9},"Muhammad Safeer Hussain",{"name":445,"orcid":446},"Muhammad Imran","https:\u002F\u002Forcid.org\u002F0000-0003-4072-4997",{"tldr":448,"method":449,"finding":450,"direction":109,"opportunity":451},"用遥感与GIS分析巴基斯坦萨戈达2000-2025年城市扩张及土地利用变化。","6期Landsat影像，最大似然监督分类，提取四类LULC并统计面积。","建设用地增325km²（282.6%），耕地减199km²，城市扩张大量侵占优质农田。","可结合耕地质量与作物生产力数据，量化城市扩张对农业产能的具体损失并构建预警模型。","2026-09-17T23:30:34.285631Z",{"id":454,"title":455,"url":456,"summary":457,"summary_zh":458,"content":9,"source_name":459,"source_url":456,"published_at":460,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":461,"score_detail":462,"sources":465,"tags":467,"primary_topic":471,"secondary_topics":472,"classification":473,"search_phrases":508,"slug":511,"view_count":82,"doi":512,"paper":513,"created_at":528},5395,"Strengthening Flood Resilience in Data-Sparse Agricultural Regions: A Planning Approach for Coastal Guyana","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23451582","Abstract. Coastal Guyana concentrates most of the country’s population and agricultural production in low-lying polder landscapes that are increasingly exposed to flooding from intense rainfall, sea-level rise, and deterioration of drainage and irrigation infrastructure. Engineering design and resilience planning in these settings are often constrained by limited hydrometric monitoring (discharge, water levels), incomplete documented drainage network, and restricted access to institutional datasets. This paper presents the value of using a low-information framework for flood resilience planning and preliminary hydraulic design in data-sparse agricultural regions, using the 364 km² part of Guyana’s Mahaica–Mahaicony catchment as a case study. The framework integrates (i) rainfall frequency analysis from long-term gauge records, (ii) remote sensing and global datasets (DEM and land-use\u002Fland-cover) to delineate sub-basins and screen flood impact, (iii) simplified runoff and volume-based drainage calculations consistent with rice-field storage and saturated soils, and (iv) structured stakeholder engagement to identify flood-prone areas, operational constraints, and feasible interventions. Six-sub-basins are used for developing a routing strategy to distribute runoff volumes and to explicitly incorporate upstream detention in the wetlands, thereby reducing peak flows conveyed northward through constrained canal corridors. High-level drainage canals, dedicated conveyance paths for critical sub-basins, and dual-purpose drains supporting both drainage and irrigation storage are used to determine preliminary cross-section designs, which are then assessed with 1D hydraulic modelling under tidal boundary conditions. The approach supports phased investment planning that improves flood safety, protects livelihoods, and increases agricultural reliability while aligning with national adaptation priorities.","摘要：圭亚那沿海地区集中了全国大部分人口和农业生产，地处低洼圩田景观，日益面临强降雨、海平面上升以及排水灌溉基础设施老化所带来的洪涝风险。在此类地区，工程设计与韧性规划往往受限于水文监测（流量、水位）资料不足、排水管网记录不完整以及机构数据集获取受限。本文以圭亚那马海卡—马海科尼（Mahaica–Mahaicony）流域364 km²的区域为案例，展示了在数据稀疏的农业地区采用低信息框架进行洪涝韧性规划与初步水力设计的价值。该框架整合了：(i) 基于长期测站记录的降雨频率分析；(ii) 利用遥感与全球数据集（DEM及土地利用\u002F土地覆盖）划分子流域并筛查洪涝影响；(iii) 与稻田蓄水和饱和土壤条件相适应的简化径流与基于水量的排水计算；(iv) 结构化利益相关方参与，以识别易涝区域、运行约束和可行干预措施。研究将流域划分为六个子流域，用于制定汇流路径策略，以分配径流量并明确纳入上游湿地滞蓄，从而削减通过受限渠廊向北输送的峰值流量。基于高位排水渠、关键子流域专用输水通道以及兼顾排水与灌溉蓄水的两用沟渠，确定初步断面设计，并在潮汐边界条件下采用一维水动力模型进行评估。该方法支持分阶段投资规划，在提升防洪安全、保护生计和提高农业可靠性的同时，与国家适应优先事项相衔接。","Geo-Eco-Marina","2026-10-18T00:00:00Z",70,{"impact":187,"substance":274,"depth":463,"authority":188,"freshness":21,"relevant":22,"comment":464},17,"该论文提出一种低信息条件下的防洪韧性规划框架，方法新颖，但案例位于圭亚那，对我国三农信息化的直接参考价值有限，因此不宜进入每日精选。",[466],{"name":459,"url":456},[27,49,468,469,470],"气候适应","防洪韧性","灌排设施",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":474},{"candidates":475,"agricultural_evidence":46},[476,480,487,494,500,504],{"code":33,"score":413,"supported":46,"title":477,"abstract":478,"tags":479},[],[49,50],[49],{"code":481,"score":55,"supported":46,"title":482,"abstract":483,"tags":486},"A1",[],[484,485],"稻田","rice",[],{"code":488,"score":55,"supported":46,"title":489,"abstract":490,"tags":493},"H3",[],[491,492],"灌溉","irrigation",[],{"code":495,"score":307,"supported":46,"title":496,"abstract":497,"tags":499},"H7",[],[498],"洪涝",[468],{"code":54,"score":63,"supported":46,"title":501,"abstract":502,"tags":503},[],[58],[],{"code":74,"score":22,"supported":14,"title":505,"abstract":506,"tags":507},[],[],[27],[509,510],"Guyana Mahaica Mahaicony 洪水","沿海稻田 排水规划","GuyanaMahaicaMahaicony洪水-5395","10.5281\u002Fzenodo.23451582",{"doi":512,"openalex_id":514,"authors":515,"venue":459,"cited_by_count":82,"oa_url":456,"card":523,"direction":109,"ingested_from":111},"W7222952224",[516,518,520],{"name":517,"orcid":9},"Omesh Persaud",{"name":519,"orcid":9},"Colis Allen",{"name":521,"orcid":522},"Ioana Popescu","https:\u002F\u002Forcid.org\u002F0000-0002-1009-5424",{"tldr":524,"method":525,"finding":526,"direction":261,"opportunity":527},"提出低信息框架，为数据稀缺农业区规划洪水韧性并做初步水力设计。","降雨频率分析、遥感DEM与土地利用、简化径流计算、利益相关者参与及一维水力模型。","上游湿地滞蓄与分区排水可降低峰值流量，支撑分阶段投资规划。","可探索低监测区遥感与参与式数据融合的洪水韧性规划方法及作物淹水风险量化。","2026-10-20T23:30:19.345049Z"]